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Evidence of cascading ecosystem effects following the loss of white sharks from False Bay, South Africa

Neil Hammerschlag, Yakira Herskowitz, Chris Fallows, Thiago B. A. Couto

2025Frontiers in Marine Science12 citationsDOIOpen Access PDF

Abstract

Top predators can affect the density (Creel et al. 2005), physiology (Leach andTaylor 1977, Woodley &Peterson 2003), and behavior (Werner et al. 1983) of prey. Such direct impacts on prey may indirectly impact multiple trophic levels (Ripple et al. 2001, Croll et al. 2005, Hammerschlag et al. 2019). Apex predators are among the most threatened species globally, experiencing widespread global population declines (Ripple et al. 2014). Accordingly, this has led to a growing concern for and need to understand the associated ecological consequences of apex predator loss on food webs (Estes et al. 2011).Sharks are upper-level predators in virtually all marine environments (Cortes 1999).Research has shown that spatial and temporal variations in shark presence has the potential to alter the abundance and behavior of their prey, indirectly impacting habitat structure (reviewed by Dedman et al. 2024). For example, on a Fijian coral reef, Rasher et al. (2017) found that differences in topography and tidal state created patches of reef that varied spatially and temporally in shark presence. At locations and times where shark encounter rates were high, herbivorous fish reduced grazing activity. This predator-driven alteration to fish behavior created spatial refuges for seaweed from grazing, resulting in higher seaweed biomass (Rasher et al. 2017). In light of global shark population declines from overfishing, understanding and predicting the consequences of shark loss on ecosystems been identified as a research priority (Jorgenson et al. 2022, Dedman et al. 2024). However, empirical evidence of the ecological impacts of large shark declines on prey populations in the wild are limited (Ruppert et al. 2013;Barley et al. 2017a,b, Hammerschlag et al. 2018, 2019, 2022) and may be context-dependent (Sandin et al. 2022). For example, on the great barrier reef, Desbiens et al. (2021) did not find an impact of shark density on either density or biomass of teleost mesopredators and prey; instead, many functional groups, including sharks, 4 were more associated with environmental drivers. Moreover, evidence for indirect cascading ecosystem effects of shark removals across multiple trophic levels is scarce (Ferretti et al. 2010, Myers et al. 2007). These knowledge gaps likely stem from the methodological, logistical, and financial challenges of conducting experimental research on large, highly mobile predators in vast marine environments (Hammerschlag 2019).Here we evaluated a unique dataset collected as part of a 20+ year monitoring program from False Bay, South Africa, which documented the decline and ultimate disappearance of white sharks (Carcharodon carcharias) from the system (Hammerschlag et al. 2019(Hammerschlag et al. , 2022)). While the exact reason behind the loss of white sharks from False Bay is unclear (Gennari et al. 2024), known removals of white sharks by the KwaZulu-Natal Sharks Board's lethal shark control program are high enough to drive regional population declines (Bowlby et al. 2022). Although not yet recorded from False Bay, instances of white shark mortality due to specialized shark-eating orcas (Orcinus orca) have been documented elsewhere along the coastline (Towner et al. 2022), likely contributing to the decline (Gennari et al. 2024).In False Bay, standardized boat-based surveys of white shark sightings at Seal Island occurred between 2000-2020 providing a metric of relative abundance over time based on the number of individual white sharks sighted per hour of observational effort (Skubel et al. 2018, Hammerschlag et al. 2019). The overall trend in the relative abundance of white sharks was relatively stable in the first fifteen years of monitoring; however, their relative abundance began to precipitously decline after 2015, leading to a complete disappearance of white sharks from the standardized surveys since mid-2018 (Hammerschlag et al. 2022). This rapid decline and subsequent loss of white sharks from False Bay coincided with rapid behavioral and physiological response in their prey, Cape fur seals (Arctocephalus pusillus pusillus), including reductions in seal stress levels and increasing seal rafting distances from Seal Island, a behavior that would have rendered seals vulnerable to shark attack (Hammerschlag et al. 2022). The loss of white sharks from False Bay also coincided with the novel emergence of sevengill sharks (Notorynchus cepedianus) in boat-based surveys at Seal Island (Hammerschlag et al. 2019). Historically, this large-bodied shark would have been an important prey of and competitor with white sharks in False Bay.Based on ecological theory, here we investigated for potential trophic cascades resulting from the rapid decline and loss of white sharks in the system. Given established predator-prey dynamics in False Bay, we hypothesized that the loss of white sharks in the system would coincide with increases in the relative abundances of Cape fur seals and sevengill sharks, which in turn would be associated with decreases in the relative abundances of their prey, such as small pelagic fishes in the case of seals and smaller benthic sharks in the case of sevengill sharks.Located off South Africa, False Bay is nearly 1000 km 2 (Pfaff et al. 2019;Fig. 1).Historically, white sharks could be found year-round in False Bay, spending more time within inshore areas during warmer months, while during colder months spending relatively more time patrolling the waters surrounding Seal Island, a rocky outcrop situated 10 km off the Bay's northern shoreline (Kock et al. 2013). Seal Island may be inhabited by as many as 60,000 Cape fur seals that were targeted prey of white sharks during colder months, whereas white sharks more time within inshore areas during warmer months (Kock et al. 2013), presumably to increase 6 foraging on large teleosts and elasmobranchs, such as sevengill sharks (Martin et al. 2005, Kock et al. 2013).Between 2000 and 2020, shark relative abundance at Seal Island was monitored from standardized boat-based observation surveys (details in Hammerschlag et al. 2019). While surveys occurred year-round, most observations occurred during colder months (May through September) (Hammerschlag et al. 2006, Fallows et al. 2012). During boat-based surveys, sharks were attracted to the boat using a line baited with fish and/or a seal decoy. Individual sharks were identified based on a combination of visual makers, including unique scarring, presence/absence of claspers, and individual variation in pigmentation patterns on the gill flaps, pelvic fins, and caudal fins. The duration of each baited survey was recorded, along with the number of different individual sharks observed during this period. Using these data, the number of different individual sharks observed per hour of baited survey was calculated as a metric of shark relative abundance (Hammerschlag et al. 2019). We used these data to calculate annual means of shark relative abundance at Seal Island, as well as overall means in the period prior to and following the decline of white sharks from False Bay (2000-2015 vs 2016-2020, i.e. pre-loss vs post-loss period).Sightings data of Cape fur seals in False Bay were derived from the Global Biodiversity Information Facility (GBIF.org) database (Telenius, 2011). Only geo-referenced occurrences deriving from 'Human Observation' and those occurring within or along the coastline of False Bay were selected, producing reports on Cape fur seal sightings by location and date. The majority of these GBIF data were derived from the iNaturalist citizen science application. Because few reports included the number of individual seals observed at a given time, we focused our analysis on the number of reports of seal sightings, rather than the number of seals observed across reports. The number of visitors to False Bay are likely to influence the number of seal sightings reported to iNaturalist and GBIF (i.e., more visitors equates to more reports). To address this, we obtained data on the number of visitors to the Cape Point Nature Reserve, which spans the western shoreline of False Bay. These data were derived from Wesgro Research (http://www.wesgro.co.za/) sourced from South African Tourism and Table Mountain National Park. While visitor data from the Cape Point Nature Reserve may underestimate the total number of visitors to False Bay, it serves as a reliable relative proxy as the number of visitors to the Cape Point Nature Reserve will scale with the number of visitors to False Bay. It also stands to reason that individuals visiting a nature reserve would be more likely to report natural observations of wildlife to citizen science databases, such as those used here. Thus, to evaluate if sightings of seals have increased over time, we calculated the annual number of seal reports to GBIF divided by the number of annual visitors to the Cape Point Nature Reserve as a standardized proxy of relative seal occurrence in False Bay over time and space. Visitor data were only available beginning 2009, therefore we focused on data from 2009 to 2022. To also evaluate if the spatial distribution of seal sightings has changed across the width of False Bay over time, we calculated the annual longitudinal range in reported seal sightings by subtracting the minimum and maximum longitudinal value of reported seal sightings by year.We then plotted the longitudinal degree range of seal sightings annually, from 2009 to 2022.BRUVS were deployed in False Bay in both the pre-loss and post-loss period using the same methods and equipment of De Vos et al. (2015a). Each BRUVS consisted of a GoPro HD camera fixed to a metal base, facing a perforated PVC bait canister (130 mm × 110 mm with 10 mm perforations). The bait-facing camera was positioned 1 m away from the bait canister, which was filled with 1 kg of chopped sardine (Sardinops sagax). For deployments, BRUVS were lowered to the seafloor via a retrievable float line and left for at least 65 minutes. The footage retained for analysis was standardized to 60 minutes, starting from the moment the BRUVS settled on the seafloor (De Vos et al. 2015a).As outlined in De Vos et al. (2015a) False Bay was divided into nine sampling zones, each encompassing a range of depths and habitats to facilitate deployment of BRUVS (Fig. 1). BRUVS were deployed in depths of 5 to 50 m, as visibility was compromised in shallower depths due to turbulence and insufficient light at deeper depths. Deployment site selection followed a random stratified design to ensure that each zone, depth range, and habitat type was sampled during winter and summer of both periods. The number of deployments chosen for each zone was proportional to the size of the zone, with fifty percent of deployments within each zone allocated to reef and sand, respectively (see De Vos et al. 2015a for more details). The minimum distance between daily sampling sites was restricted to a minimum of 250 m, but averaged 500 m, to permit statistical independence of deployments (Cappo et al. 2001;Cappo et al. 2003) and to reduce the chance of overlapping bait plumes (Bernard and Götz 2012).Between June and December of 2012, 173 BRUVS were deployed in False Bay (summer = 85, winter=88), comprising pre-loss period sampling (Fig. 1). Between July 2020 and February 2021, 150 BRUVS were deployed (summer=82, winter=68), comprising post-loss period sampling (Fig. 1). Videos from each deployment were analyzed for MaxN, which is the maximum number of individuals of the given species in any single frame for the duration of the 60-minute video at a site (Albano et al. 2021). This provided a value of MaxN per hour for each deployment that was then averaged across samples, providing a metric of relative abundance (Cappo et al. 2001, Cappo et al. 2003) While BRUVS tend to under-sample larger-bodied shark species (Santana-Garcon et al. 2014, Albano et al. 2021), possibly due to the type and amount of bait used (1 kg of sardines), any white sharks or sevengill sharks recorded on the BRUVS were analyzed for MaxN as a means of independently corroborating patterns found in the boat-based surveys. We primarily used BRUVS data to examine for changes in relative abundance of important prey for seals and sevengill sharks.Based on David (1987) and Huisamen et al. (2023), important prey for seals that were also detected on our BRUVS was Cape horse mackerel (Trachurus capensis). Based on Ebert et al. (1991) important prey for sevengill sharks in the region that were also detected in our BRUVS were pyjama catsharks (Poraderma africanum) and smoothound sharks (Mustelus mustelus).For these focal prey species, we tested for potential differences between periods in MaxN by fitting a zero-inflated Generalized Linear Mixed Model (GLMM) using the R package 'glmmTMB' (Brooks et al. 2017). Since previous work in False Bay by DeVos et al. (2015a) revealed differences in the seasonal occurrence of these lower-trophic level species (Cape horse mackerel and smoothound shark = summer; pyjama catshark = winter) as well as habitat preferences for two of the species (smoothound sharks = sand, pyjama catsharks = reef), we modelled individual counts in the form of MaxN as a function of the period (pre-loss vs post-loss of white sharks), sampling season (summer vs winter) and sampling habitat (reef vs sand), including an interaction between period and season. We incorporated sampling zone as a random 10 effect in our models to account for any potential spatial effects and variability on occurrences of the focal prey species. See the Supplementary File 1 for additional details about the GLMMs.Additionally, from each sampling method (boat-based surveys, seal sightings, BRUVS), we calculated percent change and percent difference in average metric values between periods using the following formulas:% change = [V 2 -V 1 / V 1 ] x 100, % difference = [V 2 -V 1 / ((V 2 + V 1 /2))] x 100,where V i and V 2 are the average value of relative abundance for given species in the pre-loss versus post-loss period. Analyses, calculations, and plots were completed using R Version 4.2.2 (R Core Team 2000 and the pre-loss white shark relative abundance in boat-based surveys averaged shark sightings per whereas between to 2020 as the post-loss white shark relative abundance to per hour (Fig. a and difference between periods (Fig. white sharks were sighted in False Bay since While BRUVS likely sampled white sharks, from our deployments False Bay those from the boat-based surveys at Seal Island (Fig. while only white sharks were detected on these only occurred in the pre-loss period with of white sharks on BRUVS deployment in the post-loss period with the decline of white sharks, seal observations reported from False Bay have increased over the same period (Fig. growing from a of reported seal sightings per visitors to the during the pre-loss period to in the loss period (Fig. a increase and a difference between periods (Fig. both visitor at the Cape Point Nature Reserve and reported seal sightings in 2020, likely due to and associated on which would likely File However, in 2021, to the nature reported seal sightings a File This may be by a of which more and associated wildlife while few the Cape Point Nature Reserve File In to increases in the of reported seal sightings in the post-loss the spatial of reported seal sightings has across the width of False Bay (Fig. For example, all reported seal sightings only of in but increased to of in 2019, an increase of both the number of reported seal sightings and the spatial of these sightings were relatively for the documented of white shark after which values began to increase Supplementary File fur seals in the region primarily on small pelagic such as and to a Cape horse While were not detected in our Cape horse mackerel Cape horse mackerel have been found to be among the most fish species detected in BRUVS within our region et al. with changes in seal sightings between we detected a in the relative abundance of Cape horse mackerel on our BRUVS (Fig. a and difference between the post-loss periods (Fig. This occurred primarily in the Cape horse mackerel were most in False Bay (De Vos 2021). summer relative abundance from a MaxN of in the pre-loss period to during the a decline and difference (Fig. This decline as in the zero-inflated where a interaction between period and season was detected 2 = = Cape horse mackerel are prey of seals in False Bay these are with a trophic from on seals due to the loss of white a in with changes in seal and reductions in seal physiological stress levels associated with the declines of white sharks in False Bay (Hammerschlag et al. sharks were not observed in boat-based surveys at Seal Island in the pre-loss but averaged sightings per hour following the decline of white sharks from the system (Fig. the relative abundance of sevengill sharks detected on BRUVS was with the from the boat-based data (Fig. For two important prey species of sevengill sharks detected in our BRUVS catsharks and smoothound sharks), we found reductions in relative abundance that by and between a and difference (Fig. to the for Cape horse declines for both species primarily occurred in winter for pyjama catshark and summer for For pyjama winter relative abundance from in the pre-loss period to a of during the period (Fig. a decline and % difference between periods (Fig. This decline also as in the where a interaction between period and season was detected 2 = = For smoothound sharks, their summer relative abundance from in the pre-loss period to during the period (Fig. a decline and difference between periods (Fig. The interaction between period and season did not as in the for smoothound 2 = = analysis a change for the species during the summer prey species horse pyjama and known to seasonal differences in their of False Bay (De Vos et al. De Vos 2021). we primarily detected declines between periods in the in which these species were more in False Bay. It is that their predators and sevengill are primarily these prey species during the in which their prey are most Accordingly, would as would be the by prey, which would our Such patterns have been found in predator-prey For example, with and in have revealed higher by during the season by increased prey not by increased predators and 2019). Moreover, observations of in that seasonal changes in prey abundance and their to during of increased abundance et al. that changes in species relative abundance found here following the loss of white sharks are likely not or primarily due to in but are also a of behavioral associated with to will reduce of by increasing and/or foraging behavior (Werner et al. 1983) as has been documented in the case of white sharks and seals De Vos et al. we that increases in species relative abundance patterns are also by increased foraging behavior and/or in the post-loss period associated with We that given the relatively time over which white sharks were from False Bay, the observed changes across trophic levels are likely more by changes in trophic that the of effects of predators are at trophic levels the food et al. and et al. were with this ecological (Fig. with the in relative differences between post-loss periods recorded in seals and sevengill sharks, with a relatively in relative differences in trophic of any in the wild is that our could be by including species, and natural However, for the species evaluated we found patterns that were with population in the region that we would our For example, we documented a increase in the and spatial scale of seal sightings in the post-loss the seal population in False Bay been on a since the et al. 2013). We that seal sightings data are on via citizen science that have likely more due to in more However, the number of have increased since 2009 et al. 2022), which is with the patterns of reported seal sightings documented which only began to increase following the loss of white shark from False Bay after we documented a in the relative abundance of Cape horse mackerel during the post-loss a that the of this species for the South African coastline is and that biomass are well with per effort of abundance in at on in South a with the documented in our BRUVS in the post-loss period. of data from False Bay, reported temporal in relative abundance for or pyjama catsharks between and whereas increases were found for et al. 2013). Although these time our those reported in and from the changes between periods found for these species in the for sharks, data a regional population decline et al. 2019). declines due to increased are likely by regional population declines from False Bay has over the years with associated increases in that has likely lethal and impacts on species (Pfaff et al. this is to have the observed patterns in relative abundance and at trophic Since the False Bay has also increased and which has led to of the and subsequent increases in pelagic and species (Pfaff et al. 2019). While these changes have likely ecosystem impacts in False these impacts our by and would likely have prior to the is a of fish behavior and could in to changes in the relative abundance of the observed species. However, changes in between the periods would not be to drive the observed patterns in relative abundance of predators and prey at trophic While are most by the loss of white sharks from False Bay, a of this is that for species evaluated using we only have two sampling and account for potential changes in While in our was by multiple for species sevengill sharks), the of or data that would patterns for species horse are Accordingly, work would from additional sampling over decline in white sharks that occurred in False Bay within a monitoring program has provided an to into ecological changes in the wild due to the loss of a marine apex The documented changes in relative abundance patterns between periods with of a trophic by the loss of from white This has included increases in species that were important prey of white sharks and in decreases in abundances of their work at this site would from understanding if and structure and function may have been and the to which will to change through impacts of apex predator declines are to in the in marine are likely more widespread than given the and of apex predator declines

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BayFisheryEcosystemWhite (mutation)GeographyOceanographyEnvironmental scienceEcologyBiologyGeologyBiochemistryGeneIchthyology and Marine BiologyFish Biology and Ecology StudiesFish Ecology and Management Studies